Data-Driven Uncertainty Reduction in Geotechnical Engineering: Optimal Preloading of a Road Embankment

Projekt:

BIG A2020-03 Beslutsteori i geotekniken – etapp 1: optimal överlast

Sammanfattning:
Decision making in geotechnical engineering is characterized by considerable uncertainty.
To find optimal solutions in such an environment, an iterative decision-making process, which includes
new information as it becomes available, is required. In this contribution we extend the risk-based
framework of Bismut et al. (2023) for optimal planning of a geotechnical construction to include
predictions, which are based on a linear regression analysis of monitoring data. This approach is
illustrated for the design of a surcharge on an embankment in clayey soil, as the optimal preloading
sequence is searched. We demonstrate that by increasing the amount of information considered more
cost efficient strategies can be identified and outcome uncertainties can be reduced.

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Författare: D. Cotoarba, E. Bismut, J. Spross, D. Straub
Utgivare: 14th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP14
Utgivningsdatum: 2023-07-09
Diarienummer: TRV 2020/48425
Antal sidor: 8
Språk: Engelska
Kontaktperson: Kenneth Viking, IVta4